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Develop full-stack features for the AI Catalog/Solution Registry web application using Next.js, React, and TypeScript, spanning UI, API, and data models. Build agents, skills, and MCP servers to expose Solution Registry capabilities like registering, discovering, and linking assets. Design channel-agnostic APIs to support web apps, coding-assistant integrations, and chat/search surfaces efficiently. Implement agent-facing web app experiences, including AIRB review flows and asset visualizations, powered by real data and recommendations. Deliver integrations for enterprise chat/search platforms (Teams, Slack) using their respective bot frameworks, leveraging existing backend capabilities. Develop MCP tools with robust authentication, scoping, and auditing, and build the necessary front-end and back-end components to display governance status. Create evaluation and observability tools, including the backend harness for scoring agent behavior and the UI for reviewers. Collaborate daily within AI coding assistants and contribute to tooling for other engineers. Partner with platform, security, and governance teams to ensure data model, API, and UI decisions are compliant by design.

Requires a minimum of 4 years of full-stack production engineering experience, with proficiency in modern front-end frameworks like React/Next.js and TypeScript, as well as backend services using Python or Node/TypeScript. Demonstrated experience in designing and consuming REST/GraphQL APIs, maintaining schema and versioning discipline. Hands-on experience building with or on top of Large Language Models (LLMs) such as agents, RAG, prompt-based features, or tool-calling in a shipped product. Proficiency with cloud deployment environments (AWS, Azure, or GCP) and standard web application infrastructure, including containers and CI/CD pipelines. Experience building MCP servers or similar tool/plugin integrations for LLM agents. Familiarity with integrating enterprise chat/search bot frameworks like Teams, Slack, and their connectors. Proven ability to build internal admin/review tooling for governance or compliance workflows, such as approval flows and audit views. Comfortable owning feature development end-to-end, from data model to API to UI, without requiring dedicated backend or frontend counterparts for every task. Familiarity with SQL/relational data modeling for registry-style entities (solutions, assets, governance metadata). Comfortable with evaluation frameworks for non-deterministic systems like agents.